NCT07782320Not yet recruiting
Generative AI-Based Health Education for Older Adults With Sarcopenic Obesity
An Exploration of Health-Promoting Effects of Personalized AI-Generated Multimedia Health Education in Community-Dwelling Older Adults With Sarcopenic Obesity
Source: ClinicalTrials.gov · Last updated 24 Aug 2026
Brief summary (registry, in English)
Sarcopenic obesity is a major public health concern among community-dwelling older adult populations.Encouraging healthy behavior modification through health education emerges as an effective strategy for preventing and treating sarcopenic obesity. Generative Artificial Intelligence (AI) offers an innovative opportunity to tailor health education for aging populations. This study aims to explore the effectiveness of Personalized AI-generated Multimedia Health Education in community-dwelling older adults with sarcopenic obesity. The study comprises two phases, with 280 participants in Study 1 and 180 in Study 2.Study 1, a cluster randomized controlled trial, explores the feasibility, acceptability, and efficacy of different AI-generated multimedia, including images, sounds, and videos. Study 2 employs a three-armed,individually randomized controlled trial design, creating Personalized AI-generated Multimedia Health Education based on participant preferences. All materials focus on behavioral risk factors, delivered by social media-based AI chatbots. The intervention is conducted once a day, five days a week for 12 weeks.Structured questionnaires and objective instruments collect data before and after the intervention. The study outcome includes behavioral and psychological factors, quality of life, and sarcopenic obesity indicators. Statistical analyses include descriptive analyses, Chi-square tests, t-tests, One-way analysis of variance, path models, and generalized estimating equations. This study anticipates that Personalized AI-generated Multimedia Health Education will be a feasible, acceptable, and effective intervention for older adults. The study results are expected to demonstrate a significant improvement in study outcomes in the experimental group. Personalized AI-generated multimedia health education could be an easy-to-use,enjoyable, and effective strategy for health promotion and sarcopenic obesity prevention.
- Status (registry)
- Not yet recruiting
- Study type
- Interventional
- Enrollment
- 500 (estimated)
- First submitted
- 16 Aug 2026
- Start date
- 1 Oct 2026
- Primary completion date
- 31 Dec 2029
- Lead sponsor
- Taipei Medical University
- Diseases
- Obesity
- NCT number
- NCT07782320
What you commit to
- Study type: Interventional
- Planned participants: 500
- From 1 Oct 2026 to the primary completion date, 31 Dec 2029
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Other illness
- . Presence of serious diagnosed diseases, disabilities, or mental health issues requiring medical treatment that might influence the study process.
Other
- . Functional dependency
- . Current residence in long-term care facilities or hospitals
Who the study is looking for
- . Age: 60 years or older
- . Smartphone ownership with internet connectivity
- . Appendicular fat-free mass (AFFM) calculated by the equation: AFFM = 14.529 + (17.989 \* height)+ (0.1307 \* fat mass). The cut-off value corresponds to a residual ≤ 3.4 in the equation
- . Ability to read, listen, and understand health education materials with normal cognitive function (MMSE score ≥ 25) and normal sensory function.
Age in the registry: 50 years to 99 years · Sex: All · Accepts healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Taipei Medical University Coordinator of this site? Confirm its status | Taipei | Taiwan | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.